Theoretical and experimental study of uncertain set based moving target localization using multiple robots
Feng Gu, Zheng Wang, Yuqing He, Jianda Han, Yuechao Wang · 2011
In this paper, multiple robots cooperation based moving target localization problem is researched. Different from traditional statistics based architecture, the concept of uncertain set is utilized in this paper to formulate the so called Cooperative Enhanced Set Membership Filter based cooperative localization algorithm. One of the most attracting advantages of this method is that it assumes the measurement errors are modeling as unknown-but-bounded set, instead of requiring the errors' covariance to be obtainable beforehand, which is general in statistics based algorithm, such as Kalman Filter and Particle Filter. Furthermore, some strategies, which is originated from the update process of the ESMF algorithm itself, are proposed to improve the computational efficiency and localization accuracy. Finally, an original experimental scenario is designed with respect to an indoor multiple-rotorcraft-platform and the results are listed out and analyzed in detail to verify the feasibility and validity of the proposed algorithm.